afiqzudinhadi/linkedIn_auto_jobs_applier_with_AI
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Added support for Ollama running locally or publicly hosted api

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user 2024-08-31 20:19:33 +02:00
parent 6f3b3252ba
commit d964f599be
5 changed files with 34 additions and 17 deletions
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25
src/gpt.py
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@ -3,7 +3,7 @@ import os
import re
import textwrap
from datetime import datetime
from typing import Dict, List
from typing import Dict, List, Union
from pathlib import Path
from dotenv import load_dotenv
from langchain_core.messages.ai import AIMessage
@ -11,6 +11,7 @@ from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompt_values import StringPromptValue
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from langchain_ollama import ChatOllama
from Levenshtein import distance
import src.strings as strings
@ -20,7 +21,7 @@ load_dotenv()
class LLMLogger:
def __init__(self, llm: ChatOpenAI):
def __init__(self, llm: Union[ChatOpenAI, ChatOllama]):
self.llm = llm
@staticmethod
@ -78,12 +79,12 @@ class LLMLogger:
class LoggerChatModel:
def __init__(self, llm: ChatOpenAI):
def __init__(self, llm: Union[ChatOpenAI, ChatOllama]):
self.llm = llm
def __call__(self, messages: List[Dict[str, str]]) -> str:
# Call the LLM with the provided messages and log the response.
reply = self.llm(messages)
reply = self.llm.invoke(messages)
parsed_reply = self.parse_llmresult(reply)
LLMLogger.log_request(prompts=messages, parsed_reply=parsed_reply)
return reply
@ -113,10 +114,18 @@ class LoggerChatModel:
class GPTAnswerer:
def __init__(self, openai_api_key):
self.llm_cheap = LoggerChatModel(
ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4)
)
def __init__(self, openai_api_key, openai_api_free_hosted_url):
if openai_api_key == "":
print('Using locally hosted mistral:v0.3')
self.llm_model = ChatOllama(model = "mistral:v0.3", temperature = 0.4, num_predict = 256)
elif openai_api_key == "freehosted":
print('Using free hosted gpt-4o-mini')
self.llm_model = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key="anything", temperature=0.4,
base_url=openai_api_free_hosted_url)
else:
print("Using gpt-4o-mini")
self.llm_model = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4)
self.llm_cheap = LoggerChatModel(self.llm_model)
@property
def job_description(self):
return self.job.description